The Heterogeneous Non-resident Student Body: Measuring the Effect of Out-Of-State Students’ Home-State Wealth on Tuition and Fee Price Variations

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• 作者：Manuel S. González Canché
• 关键词：Spatial econometrics ; Geospatial statistics ; Statistical analysis ; Finance in higher education ; Heterogeneous non ; resident student body ; Tuition ; price setting ; Tuition revenue ; Enrollment management
• 刊名：Research in Higher Education
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：58
• 期：2
• 页码：141-183
• 全文大小：
• 刊物类别：Humanities, Social Sciences and Law
• 刊物主题：Higher Education;
• 出版者：Springer Netherlands
• ISSN：1573-188X
• 卷排序：58

文摘

More than 40 years of research has found a positive relationship between increases in the proportion of non-resident students enrolling in an institution and increases in the tuition prices this institution charges to these same students. Notably, this line of research has consistently treated this non-resident student body as if they constitute a homogeneous group in terms of their socioeconomic well-being, when in reality these students come from states with differing levels of socioeconomic prosperity. Notably, given that tuition and fee charges to non-resident students are market-based, institutions charge what out-of-state students are willing to pay. Under this rationale, it follows that the wealthier the student body of an institution is, the more institutions will be able to charge them in terms of tuition and fees for their education. The purpose of this study is twofold. First, it offers a method to measure the level of wealth of the non-resident student body enrolling at an institution considering the level of wealth of these students’ home states, therefore creating a measure of heterogeneity of the non-resident student body. The second purpose is to evaluate whether this measure of heterogeneity is associated with larger increases in the net tuition and fee prices charged to these students compared to the increases related to the homogeneous structure that ignores these students’ home-state wealth. This twofold purpose was addressed utilizing a dataset built from regional, state, and institutional information of 1743 public and private not-for-profit 4-year institutions across the contiguous United States. Since all the outcome variables were found to be spatially dependent, spatial econometrics techniques were employed for model estimation. Results corroborated that treating non-resident students as a homogeneous structure rendered downwardly biased estimates of institutions’ abilities and/or decisions to set higher or lower tuition and fee prices compared to the estimates obtained using the heterogeneous structure. Considering current general disinvestment of states in higher education, the analysis of factors driving non-resident tuition and fee price-setting has become especially relevant for public policy officials and decision-makers at both the institution- and state-levels. Accordingly, this study examines a critical issue in the finance of higher education—the setting of institutional tuition and fees for non-resident students.